Combining stable isotope analysis and conventional techniques to improve knowledge of the diet of the European Roller Coracias garrulus

Diet studies are crucial for understanding the ecology and evolution of species, as well as for establishing appropriate conservation and management strategies. However, they remain methodologically challenging due to variation between seasons, sites, sexes or age groups and even variation between individuals. Due to method-specific characteristics and biases, a combination of existing techniques can overcome the inherent limitations of each technique and provide a more accurate and broad picture of species’ food preferences. Here, we examine diet information obtained using three different assessment methods to better understand the trophic ecology of the European Roller Coracias garrulus, a species targeted by conservation measures in Europe. First, we analysed regurgitated pellets and video recordings to report the diet composition of adult and nestling Rollers, respectively. Secondly, we used stable isotope analysis (SIA) to investigate adult sexual diet segregation as well as to confirm the main findings regarding adult and nestling diets obtained through conventional methods. Based on the analysis of pellets, the diet of adult Rollers was dominated by Coleoptera, while camera images revealed that the diet of nestlings was dominated by Orthoptera, mainly grasshoppers and bush crickets. Blood isotopic signatures of adult and nestling Rollers confirmed the results obtained through pellet and video recording techniques. Of the 45 three methods, pellet analysis contained the most comprehensive trophic information regarding the detectable prey spectrum and prey species contribution, and also provided basic diet information to inform the SIA. Our results also highlight the potential of SIA for assessing intra-specific variation in diet by sampling individuals of known age and sex, which is often unfeasible through conventional approaches. SIA analysis showed no differences in δ13C and δ15N ratios of blood between males and females and a high degree of overlap amongst isotopic niches, suggesting no sex-specific partitioning in resource use. Overall, we showed that the combination of different methods could be used to gain new and clearer insights into avian trophic ecology that are essential for informing habitat management aiming to improve availability of foraging resources

Landscape determinants of European roller foraging habitat: implications for the definition of agri-environmental measures for species conservation

Across much of Europe, farmland birds are declining more than those in other habitats. From a conservation perspective, identifying the primary preferred habitats could help improve the foraging conditions of target species and, consequently, enhance their breeding success and survival. Here, we investigated the ranging behaviour and foraging habitat selection of the European roller (Coracias garrulus) during the breeding season in an agricultural landscape of South Iberia. The occurrence of foraging rollers was predicted to gradually increase with decreasing distance from the nest and increasing availability of perches, such as fences and electric wires. Traditional olive groves and stubble fields were positively and negatively associated with the occurrence of rollers, respectively. Additionally, analysis of hunting strikes showed that rollers highly prefer foraging in fallows rather than cereal or stubble fields. Prey surveys revealed that fallows had the highest abundance of grasshoppers, rollers’ preferred prey during chick-rearing. Pair home-ranges, obtained from 95% fixed Kernel estimators averaged 70.9 ha (range = 34–118 ha) and most foraging trips (80%) occurred in the close vicinity of the nest (<500 m). Number of chicks fledged was not affected by mean foraging distances travelled during the chick-rearing period. Overall, our results suggest that traditional extensive practices of cereal cultivation, with large areas of low-intensity grazed fallows, represent a high-quality foraging habitat for rollers and should be promoted through agri-environmental schemes within at least 1-km radius from the nest. These recommendations are targeted at the roller, but have been shown to apply broadly to several other steppe-bird species

The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web

Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA)

The BioPAX community standard for pathway data sharing

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery. © 2010 Nature America, Inc. All rights reserved

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe

The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery

The Semanticscience Integrated Ontology (SIO) is an ontology to facilitate biomedical knowledge discovery. SIO features a simple upper level comprised of essential types and relations for the rich description of arbitrary (real, hypothesized, virtual, fictional) objects, processes and their attributes. SIO specifies simple design patterns to describe and associate qualities, capabilities, functions, quantities, and informational entities including textual, geometrical, and mathematical entities, and provides specific extensions in the domains of chemistry, biology, biochemistry, and bioinformatics. SIO provides an ontological foundation for the Bio2RDF linked data for the life sciences project and is used for semantic integration and discovery for SADI-based semantic web services. SIO is freely available to all users under a creative commons by attribution license. See website for further information: http://sio.semanticscience.org